Particle filter-based prognostics: Review, discussion and perspectives

• Published in: Mechanical systems and signal processing Vol. 72-73; pp. 2 - 31
• Main Authors: Jouin, Marine, Gouriveau, Rafael, Hissel, Daniel, Péra, Marie-Cécile, Zerhouni, Noureddine
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.05.2016; Elsevier
• Subjects: Automatic Control Engineering; Automatics; Challenges; Computer Science; Diagnostic software; Implementation; Issues; Mechanical systems; Particle filters; Prognostics; Robotics; Signal processing; State of the art; Statistics; Particle filters; Issues; Challenges; Prognostics; Implementation
• ISSN: 0888-3270; 1096-1216
• DOI: 10.1016/j.ymssp.2015.11.008

Particle filters are of great concern in a large variety of engineering fields such as robotics, statistics or automatics. Recently, it has developed among Prognostics and Health Management (PHM) applications for diagnostics and prognostics. According to some authors, it has ever become a state-of-the-art technique for prognostics. Nowadays, around 50 papers dealing with prognostics based on particle filters can be found in the literature. However, no comprehensive review has been proposed on the subject until now. This paper aims at analyzing the way particle filters are used in that context. The development of the tool in the prognostics׳ field is discussed before entering the details of its practical use and implementation. Current issues are identified, analyzed and some solutions or work trails are proposed. All this aims at highlighting future perspectives as well as helping new users to start with particle filters in the goal of prognostics. •The background on particle filter is reviewed.•46 references using particle filter-based prognostics are analyzed.•Implementation issues and solutions׳ perspectives are discussed.•A synthesis of practical and conceptual issues and new proposals is proposed.